Senior ML Engineer — End-to-End Production AI in Austin

Steadily; Austin (TX); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Top market compensation + equity

3 weeks PTO + 6 federal holidays

Medical, dental, vision, life, disease

HSA, FSA

401(k)

Free snacks

Team lunches

Collaborative office culture

Job summary

Steadily in Austin, TX is seeking a Senior Machine Learning Engineer to join our Engineering & Product team. In this key role you will own the end-to-end ML lifecycle, from data exploration to production deployment, including feature engineering, model training, and monitoring in a fast-growing, in-office setting (4 days a week).

You will work across data types and own the data layer, building lightweight pipelines and dbt tables, while collaborating with product and operations to drive

Qualifications

• 5+ years of experience applying ML to production problems.
• Experience owning end-to-end ML deployment.
• Ability to work with raw data sources and build pipelines.

Responsibilities

• Own end-to-end ML lifecycle from data to production.
• Build and maintain data layer and lightweight pipelines.
• Drive ML applications to improve risk prediction and product outcomes.
• Write maintainable code in Kafka/AWS/Python stack with CI/CD.
• Collaborate with Eng, Product, Operations, Business.
• Provide metrics on model quality, bias, and performance.

Skills

ML engineering

Data pipelines

Feature engineering

Model deployment

Python

AWS

Tools

Kafka

AWS (EKS)

Postgres

Django/FastAPI

dbt

GitHub Actions

Job description

Steadily in Austin, TX is seeking a Senior Machine Learning Engineer to join our Engineering & Product team. In this key role you will own the end-to-end ML lifecycle, from data exploration to production deployment, including feature engineering, model training, and monitoring in a fast-growing, in-office setting (4 days a week).

You will work across data types and own the data layer, building lightweight pipelines and dbt tables, while collaborating with product and operations to drive